Lessons Learned From Using The MPE Processing System. Gregory J. Story HAS Forecaster NWS West Gulf River Forecast Center. It II. Enhanced MPE – somewhat of misnomer Delivered in OB 8.3 Separate program from MPE Increased resolutions Temporal - Every 5 minutes (based on VCP)
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Gregory J. Story
HAS Forecaster NWS West Gulf River Forecast Center
Problems With WSR-88D Precipitation Estimates (Why we bias the Radar)
It has been determined by the WGRFC HAS Forecasters that at least three primary things can have a great impact on the amount of rainfall that is estimated by the WSR-88D. One is radar calibration, another is proper Z-R relationships, and the third is the proper use or misuse of the WSR-88D adaptable parameters. Using MPE’s bias adjustment schemes, we attempt to mitigate the radar precipitation estimates as much as possible.
MPE Biases from WGRFC are now on the internet
First Lessons Learned from Stage III
The WFO’s in our area of responsibility can see what their radar’s bias
is in real time.
MPE Build 8 Beta Test
Over the past 10 years, the National Weather Service West Gulf River Forecast Center has been using real-time precipitation estimates produced by the WSR-88D radar. The radar precipitation estimates are very useful to the hydrometeorologists at the WGRFC for real-time rainfall estimates which in turn are used for flood prediction. Additionally, precipitation estimates using the network of GOES satellites (called the hydroestimator) has become available for use. Tools to enhance and correct the radar-derived precipitation estimates have been in use for some time now, beginning with the Stage III precipitation processing system in the 1990’s. The latest interactive program being used which optimizes the radar precipitation estimates by comparing them to hourly rain gauge reports, and by integrating the satellite precipitation estimates is called the Multisensor Precipitation Estimator (MPE) Processing System.
Recently this software has seen several additional fields added to it by the NWS Office of Hydrologic Development. The HAS forecasters at the West Gulf RFC have been using these fields during several rainfall events, including the newest fields from the AWIPS Build 8 version, which WGRFC is beta testing. I will describe what these fields are, how they are derived, and which fields appear to work the best under different types of rainfall events. I will also discuss how problems with WSR-88D precipitation algorithm settings can affect some of these fields, and ways the HAS forecasters mitigate these problems using MPE. The MPE program has also been deployed at the field offices around the country for use at the local level. To assist our field offices in their use of the software, our RFC has implemented a process to share their radars’ biases with them. This enables weather forecast office forecasters to see if their radar may be overestimating or underestimating the rainfall. This in turn assists them to issue more accurate flash flood warnings and aids them in using MPE with satisfactory results. I will illustrate how this field bias information is shared with the offices in the WGRFC area of responsibility. In addition, the Enhanced Multisensor Precipitation Estimator program is slated to be deployed at field offices in the near future. This program will use a much finer temporal and spatial resolution to provide precipitation input to the Flash Flood Monitoring and Prediction program used at NWS field offices. I will describe how MPE and EMPE are interconnected.
The Multisensor Precipitation Estimator software gave WGRFC:
1. New fields, including:
Satellite Precipitation Estimates using the NESDIS Hydroestimator
Local Bias Radar Field Mosaic
Local Bias Multisensor Field Mosaic using MPE radar climatologies
Field Bias Multisensor Field Mosaic using MPE radar climatologies
Gauge-Only Field Analysis which is normalized to PRISM data in
the absence of radar precipitation estimates
Process 3, or “P3” Field (in later builds)
Local bias satellite precipitation estimates (in later builds)
Note: The average and maximum radar field mosaics which do not use bias correction or radar climatologies were added in later builds of MPE from old Stage III
2. More robust radar bias calculation scheme
3. Radar Height Coverage Field from the radar climatologies
4. Ability to edit final precipitation estimate by drawing polygons and inserting any other field or any precipitation value in it. Very quick removal of anomalous propagation.
5. Improved Gauge Table
There are three new fields in the Build 8.2 version. They are the mergedlocal bias satellite-local bias radar mosaic, merged local bias satellite-gauge mosaic, and the merged local bias satellite-gauge-local bias radar precipitation estimate mosaic (shown above). These fields fill in the gaps with local bias satellite estimates where both rain gauge data and radar data do not exist. So far the WGRFC HAS forecasters seem to think the satellite-gauge-radar combination has the most utility.
The Future – Looking at new Precipitation Fields.
MPE Lessons Learned
Additional questions? Contact me at: